A review of algorithm & hardware design for AI-based biomedical applications
Y Wei, J Zhou, Y Wang, Y Liu, Q Liu… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
This paper reviews the state of the arts and trends of the AI-Based biomedical processing
algorithms and hardware. The algorithms and hardware for different biomedical applications …
algorithms and hardware. The algorithms and hardware for different biomedical applications …
From seizure detection to smart and fully embedded seizure prediction engine: A review
Recent review papers have investigated seizure prediction, creating the possibility of
preempting epileptic seizures. Correct seizure prediction can significantly improve the …
preempting epileptic seizures. Correct seizure prediction can significantly improve the …
Stochastic configuration machines for industrial artificial intelligence
D Wang, MJ Felicetti - arXiv preprint arXiv:2308.13570, 2023 - arxiv.org
Real-time predictive modelling with desired accuracy is highly expected in industrial artificial
intelligence (IAI), where neural networks play a key role. Neural networks in IAI require …
intelligence (IAI), where neural networks play a key role. Neural networks in IAI require …
Pediatric seizure prediction in scalp EEG using a multi-scale neural network with dilated convolutions
Objective: Epileptic seizure prediction based on scalp electroencephalogram (EEG) is of
great significance for improving the quality of life of patients with epilepsy. In recent years, a …
great significance for improving the quality of life of patients with epilepsy. In recent years, a …
An overview of EEG-based machine learning methods in seizure prediction and opportunities for neurologists in this field
B Maimaiti, H Meng, Y Lv, J Qiu, Z Zhu, Y Xie, Y Li… - Neuroscience, 2022 - Elsevier
The unpredictability of epileptic seizures is one of the most problematic aspects of the field of
epilepsy. Methods or devices capable of detecting seizures minutes before they occur may …
epilepsy. Methods or devices capable of detecting seizures minutes before they occur may …
Classification and analysis of epileptic EEG recordings using convolutional neural network and class activation mapping
Electrical bio-signals have the potential to be used in different applications due to their
hidden nature and their ability to facilitate liveness detection. This paper investigates the …
hidden nature and their ability to facilitate liveness detection. This paper investigates the …
Stochastic configuration machines: FPGA implementation
MJ Felicetti, D Wang - arXiv preprint arXiv:2310.19225, 2023 - arxiv.org
Neural networks for industrial applications generally have additional constraints such as
response speed, memory size and power usage. Randomized learners can address some …
response speed, memory size and power usage. Randomized learners can address some …
An ultra-low power reconfigurable biomedical ai processor with adaptive learning for versatile wearable intelligent health monitoring
Wearable intelligent health monitoring devices with on-device biomedical AI processor can
be used to detect the abnormity in users' biomedical signals (eg, ECG arrythmia …
be used to detect the abnormity in users' biomedical signals (eg, ECG arrythmia …
FPGA-based implementation of classification techniques: A survey
Recently, a number of classification techniques have been introduced. However, processing
large dataset in a reasonable time has become a major challenge. This made classification …
large dataset in a reasonable time has become a major challenge. This made classification …
Emerging trends of biomedical circuits and systems
Biomedical circuits and systems are heading toward a multidisciplinary race in two main
directions. On the one hand, advanced smart medical devices must be built to improve …
directions. On the one hand, advanced smart medical devices must be built to improve …